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@ARTICLE{buckner1988dim,
  author = {Buckner, J.C.},
  title = {{The development of an instrument to measure neighborhood cohesion}},
  journal = {American Journal of Community Psychology},
  year = {1988},
  volume = {16},
  pages = {771--791},
  number = {6},
  publisher = {Springer}
}

@ARTICLE{cao2001mka,
  author = {Cao, C.},
  title = {Medical Knowledge Acquisition from Encyclopedic Texts},
  journal = {Lectures In Computer Science},
  year = {2001},
  volume = {2101},
  pages = {268--271}
}

@ARTICLE{Davies1998,
  author = {N. J. Davies AND R. S. Stewart AND R. Weeks},
  title = {Knowledge Sharing Agents Over the World Wide Web},
  journal = {BT Technology Journal},
  year = {1998},
  volume = {16},
  pages = {104-109},
  number = {3},
  month = {7},
  abstract = {Large and increasing amounts of information are now available both
	on the Internet and on corporate intranets. With the availability
	of these vast networked information resources comes a requirement
	for tools to manage the information and provide users with the information
	they want, when they want it.
	
	This paper describes a system which facilitates and encourages the
	sharing of knowledge between groups of users within (or perhaps across)
	organisations. KSE (knowledge sharing environment) is a system of
	information agents for organising, summarising and sharing knowledge
	from a number of sources, including the World Wide Web, an organisation's
	internal intranet or from other users. Users are organised into closed
	user groups or communities of interest with related or overlapping
	interests. Such groups could be members of a project team, students
	studying the same subject (perhaps at different institutions), members
	of an organisational department, and so on. As well as sharing explicit
	(codified) knowledge, the sharing of tacit knowledge is encouraged
	via the automatic suggestion of, and support for, contact between
	people with mutual concerns or interests.},
  doi = {10.1023/A:1009638100845},
  owner = {Administrator},
  timestamp = {2007.08.16}
}

@ARTICLE{huang2008ipa,
  author = {Huang, Q. and Davison, R.M. and Gu, J.},
  title = {Impact of personal and cultural factors on knowledge sharing in China},
  journal = {Asia Pacific Journal of Management},
  year = {2008},
  volume = {25},
  pages = {451--471},
  number = {3},
  publisher = {Springer}
}

@ARTICLE{Mentzas2007,
  author = {Gregoris Mentzas AND Dimitris Apostolou AND Kostas Kafentzis AND
	Panos Georgolios},
  title = {Inter-organizational networks for knowledge sharing and trading},
  journal = {Information Technology and Management},
  year = {2007},
  volume = {7},
  pages = {259-276},
  number = {4},
  month = {12},
  abstract = {Although companies are increasingly developing complex networks of
	connections with their partners and customers and shifting their
	focus towards expanding the knowledge management concept externally,
	research addressing the management of knowledge across organizational
	borders is rather sparse. Our aim in the present paper is to develop
	a typology of cross-organizational networks of information and knowledge
	flows. In order to arrive at such a typology we examine two issues.
	The first concerns the locus of control on the processes that enable
	knowledge flow. The second refers to the tradability of the streams
	of knowledge that flow among organizational entities. We examine
	four types of knowledge networks: “knowledge communities”, “knowledge
	chains”, “knowledge supplies” and “knowledge markets”. For each type
	of knowledge network, we examine its distinct characteristics, study
	related examples, consider the associated research challenges and
	analyze an indicative case.},
  doi = {10.1007/s10799-006-0276-8},
  keywords = {Knowledge management - Inter-organizational networks - Collaborative
	commerce - Extended supply chain management - Knowledge flows},
  owner = {Administrator},
  timestamp = {2007.11.12}
}

@ARTICLE{raymond1999cab,
  author = {Raymond, E.},
  title = {The Cathedral and the Bazaar},
  journal = {Knowledge, Technology, and Policy},
  year = {1999},
  volume = {12},
  pages = {23--49},
  number = {3},
  publisher = {Springer}
}

@ARTICLE{Roennow-Rasmussen2002,
  author = {Rønnow-Rasmussen, Toni},
  title = {Instrumental Values – Strong and Weak},
  journal = {Ethical Theory and Moral Practice},
  year = {2002},
  volume = {5},
  pages = {23--43},
  number = {1},
  month = mar,
  __markedentry = {[fox]},
  abstract = {What does it mean that an object has instrumental value? While some
	writers seem to think it means that the object bears a value, and
	that instrumental value accordingly is a kind of value, other writers
	seem to think that the object is not a value bearer but is only what
	is conducive to something of value. Contrary to what is the general
	view among philosophers of value, I argue that if instrumental value
	is a kind of value, then it is a kind of extrinsic final value.},
  owner = {fox},
  timestamp = {2009.08.24},
  url = {http://dx.doi.org/10.1023/A:1014422001048}
}

@ARTICLE{Sestito1991,
  author = {Sestito, Sabrina and Dillon, Tharam},
  title = {Using single-layered neural networks for the extraction of conjunctive
	rules and hierarchical classifications},
  journal = {Applied Intelligence},
  year = {1991},
  volume = {1},
  pages = {157--173},
  number = {2},
  month = oct,
  abstract = {Machine Learning is an area concerned with the automation of the process
	of knowledge acquisition. Neural networks generally represent their
	knowledge at the lower level, while knowledge based systems use higher
	level knowledge representations. The method we propose here, provides
	a technique which automatically allows us to extract production rules
	from the lower level representation used by a single-layered neural
	networks trained by Hebb's rule. Even though a single-layered neural
	network can not model complex, nonlinear domains, their strength
	in dealing with noise has enabled us to produce correct rules in
	a noisy domain.},
  owner = {fox},
  timestamp = {2008.09.01},
  url = {http://dx.doi.org/10.1007/BF00058881}
}

@ARTICLE{vansteenkiste2003ccr,
  author = {Vansteenkiste, M. and Deci, E.L.},
  title = {Competitively Contingent Rewards and Intrinsic Motivation: Can Losers
	Remain Motivated?},
  journal = {Motivation and Emotion},
  year = {2003},
  volume = {27},
  pages = {273--299},
  number = {4},
  publisher = {Springer}
}

@ARTICLE{Ye2006,
  author = {Ye, Shun and Chen, Huaping and Jin, Xiaoling},
  title = {An Empirical Study of What Drives Users to Share Knowledge in Virtual
	Communities},
  journal = {Knowledge Science, Engineering and Management},
  year = {2006},
  volume = {4092},
  pages = {563--575},
  abstract = {This paper proposes and tests a new model that helps explain knowledge
	contribution in virtual communities. Grounded on a communication-based
	view, we examined key drivers of user intention to share knowledge
	in virtual communities from three aspects: the knowledge to be shared,
	the individual self and the environment. In particular, a self-concept-based
	motivation model was employed to investigate individuals’ motivational
	factors. An empirical study of 363 virtual community users demonstrated
	the salient and dominant influences of enhanced knowledge self-efficacy
	and self-image on knowledge contribution intention. Enjoyment in
	helping others, trust and system usability were also found to be
	important motivations for knowledge sharing. Implications for both
	researchers and practitioners are discussed.},
  owner = {fox},
  timestamp = {2008.10.28},
  url = {http://dx.doi.org/10.1007/11811220_48}
}

